Prior elicitation for model selection an estimation in generalized linear mixed models

Journal of Statistical Planning and Inference

Volumn 111, Issue 1-2, 2003, Pages 57-76

  Chen, Ming Hui ^a   Ibrahim, Joseph G ^b   Shao, Qi Man ^c   Weiss, Robert E ^d  

^a Worcester Polytechnic Institute   (United States)

^b IL   (United States)

^c UNIVERSITY OF OREGON   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Correlation; Gibbs sampling; Historical data; Poisson regression; Prior distribution; Random effects

Indexed keywords

EID: 0037290198     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-3758(02)00285-9     Document Type: Article

References (16)

1. Bedrick, E.J., Christensen, R., Johnson, W.O., 1996. A new perspective on priors for generalized linear models. J. Amer. Statist. Assoc. 91, 1450-1460.
2. Berger, J.O., 1985. Statistical Decision Theory and Bayesian Analysis, 2nd Edition. Springer, New York.
3. Breslow, N.E., Clayton, D.G., 1993. Approximate inference in generalized linear mixed models. J. Amer. Statist. Assoc. 88, 9-25.
4. Chen, M.-H., 1994. Importance-weighted marginal Bayesian posterior density estimation. J. Amer. Statist. Assoc. 89, 818-824.
5. Chen, M.-H., Shao, Q.-M., 1999. Monte Carlo estimation of Bayesian credible and HPD intervals. J. Comput. Graph. Statist. 8, 69-92.
6. Chen, M.-H., Ibrahim, J.G., Yiannoutsos, C., 1999. Prior elicitation, variable selection, and Bayesian computation for logistic regression models. J. Roy. Statist. Soc. Ser. B 61, 223-242.
7. Gelfand, A.E., Sahu, S.K., 1996. Identifiability, Propriety and parameterization with regard to simulation-based fitting of generalized linear mixed models. Technical Report #9636, Department of Statistics, University of Connecticut.
8. Gelfand, A.E., Sahu, S.K., Carlin, B.P., 1996. Efficient parametrisations for generalized linear mixed models (with discussion). In: J.M. Bernardo, J.O. Berger, A.P. Dawid, A.F.M. Smith (Eds.), Bayesian Statistics, Vol. 5. Oxford University Press, Oxford, pp. 165-180.
9. Gilks, W.R., Wild, P., 1992. Adaptive rejection sampling for Gibbs sampling. Appl. Statist. 41, 337-348.
10. Hobert, J.P., Casella, G., 1996. The effect of improper priors on Gibbs sampling in hierarchical linear mixed models. J. Amer. Statist. Assoc. 91, 1461-1473.
11. Ibrahim, J.G., Laud, P.W., 1994. A predictive approach to the analysis of designed experiments. J. Amer. Statist. Assoc. 89, 309-319.
12. Ibrahim, J.G., Ryan, L.M., Chen, M.-H., 1998. Use of historical controls to adjust for covariates in trend tests for binary data. J. Amer. Statist. Assoc. 93, 1282-1293.
13. Laird, N.M., Ware, J.H., 1982. Random-effects models for longitudinal data. Biometrics 38, 963-974.
14. Laud, P.W., Ibrahim, J.G., 1995. Predictive model selection. J. Roy. Statist. Soc. Ser. B 57, 247-262.
15. Natarajan, R., McCulloch, C.E., 1995. A note on the existence of the posterior distribution for a class of mixed models for binomial responses. Biometrika 82, 639-643.
16. Zeger, S.L., Karim, M.R., 1991. Generalized linear models with random effects, a Gibbs sampling approach. J. Amer. Statist. Assoc. 86, 79-86.